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accession-icon GSE27280
Pompe disease induced pluripotent stem cells for pathogenesis modeling, drug testing and disease marker identification
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pompe disease is caused by autosomal recessive mutations in the GAA gene, which encodes acid alpha-glucosidase. Although enzyme replacement therapy has recently improved patient survival greatly, the results in skeletal muscles and for advanced disease are still not satisfactory. Here, we report the derivation of Pompe disease induced pluripotent stem cells (PomD-iPSCs) and their potential for pathogenesis modeling, drug testing and disease marker identification. PomD-iPSCs maintained pluripotent features, and had low GAA activity and high glycogen content. Cardiomyocyte-like cells (CMLCs) differentiated from PomD-iPSCs recapitulated the hallmark Pompe disease pathophysiological phenotypes, including high levels of glycogen, abundant intracellular LAMP-1- or LC3-positive granules, and multiple ultrastructural aberrances. Drug rescue assessment showed that exposure of PomD-iPSC-derived CMLCs to rhGAA reversed the major pathologic phenotypes. Further, L-carnitine and 3- methyladenine treatment reduced defective cellular respiration and buildup of phagolysosomes, respectively, in the diseased cells. By comparative transcriptome analysis, we identified glycogen metabolism, lysosome and mitochondria related marker genes whose expression robustly correlated with the therapeutic effect of drug treatment in PomD-iPSC-derived CMLCs. Collectively, these results demonstrate that PomD-iPSCs are a promising in vitro disease model for development of novel therapeutic strategies for Pompe disease.

Publication Title

Human Pompe disease-induced pluripotent stem cells for pathogenesis modeling, drug testing and disease marker identification.

Sample Metadata Fields

Specimen part

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accession-icon GSE13727
PBMS cells from SJS/TEN
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis

Publication Title

Granulysin is a key mediator for disseminated keratinocyte death in Stevens-Johnson syndrome and toxic epidermal necrolysis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13726
SJS blister cells
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis

Publication Title

Granulysin is a key mediator for disseminated keratinocyte death in Stevens-Johnson syndrome and toxic epidermal necrolysis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE26646
Transcriptome profiling of LecRKVI.2 over-expressor plants.
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

The arabidopsis L-type lectin receptor kinase-VI.2 positively regulates bacterial PAMP-triggered immunity.

Publication Title

The lectin receptor kinase-VI.2 is required for priming and positively regulates Arabidopsis pattern-triggered immunity.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE30053
Dynamics of two oscillation phenotypes in S. cerevisiae reveal a network of genome-wide transcriptional and cell cycle oscillators.
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30052
Dynamics of two oscillation phenotypes in S. cerevisiae [4hr]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Genetic and environmental factors influence the phenotype of an organism. Time is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional changes in cells oscillating with ~2 and ~4 h periods. We mapped the global patterns of transcriptional oscillations into a 3-dimensional map to represent different cellular phenotypes of oscillation period. This map shows the dynamic nature of transcripts through time and concentration space, and that they are ordered and coupled to each other. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. This ordered timing of biological process may allow cells to grow energetically efficient. Decreased glucose levels in the media were found to increase the redox cycles of yeast strain CEN.PK113-7D. Glucose may have acted as signaling molecules for timing longer catabolic processes in the cell population. As oscillation period lengthened, the peak to trough ratio of transcripts increased and the percent of cells in the unbudded (G0/G1) phase of the cell cycle increased. Gene transcripts appear to be coordinated with metabolic functions and the cell cycle.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30051
Dynamics of two oscillation phenotypes in S. cerevisiae [2hr]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Genetic and environmental factors influence the phenotype of an organism. Time is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional changes in cells oscillating with ~2 and ~4 h periods. We mapped the global patterns of transcriptional oscillations into a 3-dimensional map to represent different cellular phenotypes of oscillation period. This map shows the dynamic nature of transcripts through time and concentration space, and that they are ordered and coupled to each other. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. This ordered timing of biological process may allow cells to grow energetically efficient. Decreased glucose levels in the media were found to increase the redox cycles of yeast strain CEN.PK113-7D. Glucose may have acted as signaling molecules for timing longer catabolic processes in the cell population. As oscillation period lengthened, the peak to trough ratio of transcripts increased and the percent of cells in the unbudded (G0/G1) phase of the cell cycle increased. Gene transcripts appear to be coordinated with metabolic functions and the cell cycle.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP049142
Mus musculus strain:CL57BL6x129 Transcriptome or Gene expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Identification of downstream genes of onecut transcriptions factors in the developing retina

Publication Title

Onecut1 and Onecut2 redundantly regulate early retinal cell fates during development.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP006719
ChimeraScan: A tool for identifying chimeric transcription in sequencing data
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Next Generation Sequencing technologies have enabled de novo gene fusion discovery that could reveal candidates with therapeutic significance in cancer. Here we present an open-source software package, ChimeraScan, for the discovery of chimeric transcription between two independent transcripts. Overall design: Three cancer cell lines with known gene fusions

Publication Title

ChimeraScan: a tool for identifying chimeric transcription in sequencing data.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP064574
Genetic code expansion in stable cell lines enables encoded chromatin modification
  • organism-icon Mus musculus
  • sample-icon 40 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Genetically encoded unnatural amino acids provide powerful strategies for modulating the molecular functions of proteins in mammalian cells. However this approach has not been coupled to genome-wide measurements, because efficient unnatural amino acid incorporation is limited to readily transfectable cells and leads to very heterogeneous expression. We demonstrate that rapid piggybac integration of the orthogonal pyrrolysyl-tRNA synthetase (PylS)/tRNAPyl CUA pair (and its derivatives) into the mammalian genome enables efficient, homogeneous unnatural amino acid incorporation into target proteins in diverse cells, and we reveal the distinct transcriptional responses of ES cells and MEFs to amber suppression. Genetically encoding Ne-acetyl-lysine in place of six lysine residues in histone H3, that are known to be post-translationally acetylated, enables deposition of pre-acetylated histones into cellular chromatin, via a synthetic pathway that is orthogonal to enzymatic modification, allowing us to determine the consequences of acetylation at specific amino acids in histones on gene expression. Overall design: mRNA was sequenced using polyA-enrichment and Truseq library preparation protocol. Two biological replicates were sequences for each cell line and condition

Publication Title

Genetic code expansion in stable cell lines enables encoded chromatin modification.

Sample Metadata Fields

Cell line, Subject

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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